def test_net_purchases_of_equities_is_same_in_konex(self):
# 종목명 매도거래량 매수거래량 순매수거래량 매도거래대금 매수거래대금 순매수거래대금
# 티커
# 140610 엔솔바이오사이언스 181980 222487 40507 3120731650 3812653350 691921700
# 044990 에이치엔에스하이텍 11827 47463 35636 108445380 429105250 320659870
# 246250 에스엘에스바이오 66974 89265 22291 694143600 927707350 233563750
# 058970 엠로 41594 54831 13237 687397650 916045050 228647400
# 067370 선바이오 80726 92160 11434 1512812100 1726903850 214091750
df = stock.get_market_net_purchases_of_equities_by_ticker("20210115", "20210122", market="KONEX")
temp = df.iloc[0:5, -1] == np.array([691921700, 320659870, 233563750, 228647400, 214091750])
self.assertEqual(temp.sum(), 5)
temp = df.index[0:5] == np.array(["140610", "044990", "246250", "058970", "067370"])
self.assertEqual(temp.sum(), 5)
def test_net_purchases_of_equities_is_same_in_kosdaq(self):
# 종목명 매도거래량 매수거래량 순매수거래량 매도거래대금 매수거래대금 순매수거래대금
# 티커
# 236810 엔비티 10896787 12917977 2021190 441165915800 529418663600 88252747800
# 347860 알체라 13313280 14126491 813211 498152570750 524842304250 26689733500
# 235980 메드팩토 4013688 4234321 220633 351960930900 372072449300 20111518400
# 039200 오스코텍 4720525 5104237 383712 214412650350 233303007450 18890357100
# 000250 삼천당제약 2065806 2302470 236664 138698548300 154602581800 15904033500
df = stock.get_market_net_purchases_of_equities_by_ticker("20210115", "20210122", market="KOSDAQ")
temp = df.iloc[0:5, -1] == np.array([88252747800, 26689733500, 20111518400, 18890357100, 15904033500])
self.assertEqual(temp.sum(), 5)
temp = df.index[0:5] == np.array(["236810", "347860", "235980", "039200", "000250"])
self.assertEqual(temp.sum(), 5)
def test_net_purchases_of_equities_is_same_2(self):
# 종목명 매도거래량 매수거래량 순매수거래량 매도거래대금 매수거래대금 순매수거래대금
# 티커
# 095570 AJ네트웍스 2088907 2088907 0 8914353675 8914353675 0
# 006840 AK홀딩스 1409142 1409142 0 38080803500 38080803500 0
# 027410 BGF 4987904 4987904 0 25072969705 25072969705 0
# 282330 BGF리테일 410697 410697 0 61421158500 61421158500 0
# 138930 BNK금융지주 11505016 11505016 0 66265083520 66265083520 0
df = stock.get_market_net_purchases_of_equities_by_ticker("20210115", "20210122", investor="전체")
temp = df.iloc[0:5, -2] == np.array([8914353675, 38080803500, 25072969705, 61421158500, 66265083520])
self.assertEqual(temp.sum(), 5)
temp = df.index[0:5] == np.array(["095570", "006840", "027410", "282330", "138930"])
self.assertEqual(temp.sum(), 5)
def test_net_purchases_of_equities_is_same_1(self):
# 종목명 매도거래량 매수거래량 순매수거래량 매도거래대금 매수거래대금 순매수거래대금
# 티커
# 034730 SK 456805 585912 129107 146275554500 188418240500 42142686000
# 035420 NAVER 1084406 1204178 119772 343524584000 383697248000 40172664000
# 000660 SK하이닉스 3146942 3401946 255004 409523728500 443014951000 33491222500
# 017670 SK텔레콤 433019 564491 131472 108248823000 141157900500 32909077500
# 086280 현대글로비스 306280 447356 141076 61999464500 91084909000 29085444500
df = stock.get_market_net_purchases_of_equities_by_ticker("20210115", "20210122", investor="금융투자")
temp = df.iloc[0:5, -1] == np.array([42142686000, 40172664000, 33491222500, 32909077500, 29085444500])
self.assertEqual(temp.sum(), 5)
temp = df.index[0:5] == np.array(["034730", "035420", "000660", "017670", "086280"])
self.assertEqual(temp.sum(), 5)
def test_net_purchases_of_equities_is_same_0(self):
df = stock.get_market_net_purchases_of_equities_by_ticker("20210115", "20210122")
# 종목명 매도거래량 매수거래량 순매수거래량 매도거래대금 매수거래대금 순매수거래대금
# 티커
# 005930 삼성전자 79567418 102852747 23285329 6918846810800 8972911580500 2054064769700
# 000270 기아차 44440252 49880626 5440374 3861283906400 4377698855000 516414948600
# 005935 삼성전자우 15849762 20011325 4161563 1207133611400 1528694164400 321560553000
# 051910 LG화학 709872 921975 212103 700823533000 908593419000 207769886000
# 096770 SK이노베이션 4848359 5515777 667418 1298854139000 1478890602000 180036463000
temp = df.iloc[0:5, -1] == np.array([2054064769700, 516414948600, 321560553000, 207769886000, 180036463000])
self.assertEqual(temp.sum(), 5)
temp = df.index[0:5] == np.array(["005930", "000270", "005935", "051910", "096770"])
self.assertEqual(temp.sum(), 5)
# from pykrx import stock
# import pandas as pd
# df = stock.get_market_trading_volume_by_investor("20210115", "20210122", "005930")
# print(df.head())
# # low_list = [ ]
# # tickers = stock.get_market_ticker_list()
# # print(tickers)
# # for ticker in tickers:
# # df = stock.get_market_ohlcv_by_date("20210103", "20210430", ticker)
# # low_list.append(df['저가'])
# # df = pd.concat(low_list, axis=1)
# # print(df)
import pykrx
print(pykrx.__version__)
from pykrx import stock
# df = stock.get_market_price_change_by_ticker(fromdate="20210104", todate="20210111")
# print(df)
print(stock.get_market_net_purchases_of_equities_by_ticker('20210801', '20210831', 'ALL', '기관합계'))